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Article: An efficient algorithm for finding dense regions for mining quantitative association rules

TitleAn efficient algorithm for finding dense regions for mining quantitative association rules
Authors
KeywordsAlgorithms
Data Mining
Dense Regions
Density Measure
Quantitative Association Rules
Issue Date2005
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwa
Citation
Computers And Mathematics With Applications, 2005, v. 50 n. 3-4, p. 471-490 How to Cite?
AbstractMany algorithms have been proposed for mining boolean association rules. However, very little work has been done in mining quantitative association rules. Although we can transform quantitative attributes into boolean attributes, this approach is not effective and is difficult to scale up for high-dimensional cases and also may result in many imprecise association rules. Newly designed algorithms for quantitative association rules still are persecuted by the problems of nonscalability and noise. In this paper, an efficient algorithm, DRMiner, is proposed. By using the notion of "density" to capture the characteristics of quantitative attributes and an efficient procedure to locate the "dense regions", DRMiner not only can solve the problems of previous approaches, but also can scale up well for high-dimensional cases. Evaluations on DRMiner have been performed using synthetic databases. The results show that DRMiner is effective and can scale up quite linearly with the increasing number of attributes. © 2005 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/152326
ISSN
2015 Impact Factor: 1.398
2015 SCImago Journal Rankings: 1.092
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLian, Wen_US
dc.contributor.authorCheung, DWen_US
dc.contributor.authorYiu, SMen_US
dc.date.accessioned2012-06-26T06:37:13Z-
dc.date.available2012-06-26T06:37:13Z-
dc.date.issued2005en_US
dc.identifier.citationComputers And Mathematics With Applications, 2005, v. 50 n. 3-4, p. 471-490en_US
dc.identifier.issn0898-1221en_US
dc.identifier.urihttp://hdl.handle.net/10722/152326-
dc.description.abstractMany algorithms have been proposed for mining boolean association rules. However, very little work has been done in mining quantitative association rules. Although we can transform quantitative attributes into boolean attributes, this approach is not effective and is difficult to scale up for high-dimensional cases and also may result in many imprecise association rules. Newly designed algorithms for quantitative association rules still are persecuted by the problems of nonscalability and noise. In this paper, an efficient algorithm, DRMiner, is proposed. By using the notion of "density" to capture the characteristics of quantitative attributes and an efficient procedure to locate the "dense regions", DRMiner not only can solve the problems of previous approaches, but also can scale up well for high-dimensional cases. Evaluations on DRMiner have been performed using synthetic databases. The results show that DRMiner is effective and can scale up quite linearly with the increasing number of attributes. © 2005 Elsevier Ltd. All rights reserved.en_US
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwaen_US
dc.relation.ispartofComputers and Mathematics with Applicationsen_US
dc.subjectAlgorithmsen_US
dc.subjectData Miningen_US
dc.subjectDense Regionsen_US
dc.subjectDensity Measureen_US
dc.subjectQuantitative Association Rulesen_US
dc.titleAn efficient algorithm for finding dense regions for mining quantitative association rulesen_US
dc.typeArticleen_US
dc.identifier.emailCheung, DW:dcheung@cs.hku.hken_US
dc.identifier.emailYiu, SM:smyiu@cs.hku.hken_US
dc.identifier.authorityCheung, DW=rp00101en_US
dc.identifier.authorityYiu, SM=rp00207en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.camwa.2005.03.009en_US
dc.identifier.scopuseid_2-s2.0-27344442458en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-27344442458&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume50en_US
dc.identifier.issue3-4en_US
dc.identifier.spage471en_US
dc.identifier.epage490en_US
dc.identifier.isiWOS:000231915100014-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridLian, W=22433603900en_US
dc.identifier.scopusauthoridCheung, DW=34567902600en_US
dc.identifier.scopusauthoridYiu, SM=7003282240en_US

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